From my favorite matlab blog of AngelJohnsy (click to view the rest of the article).
Clustering can be defined as the grouping of data points based on some commonality or similarity between the points. One of the simplest methods is K-means clustering. In this method, the number of clusters is initialized and the center of each of the cluster is randomly chosen. The Euclidean distance between each data point and all the center of the clusters is computed and based on the minimum distance each data point is assigned to certain cluster. The new center for the cluster is defined and the Euclidean distance is calculated. This procedure iterates till convergence is reached…
